Skip to content

Add snippets for score boosting #39

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
coszio merged 12 commits into from
Apr 22, 2025
Merged

Add snippets for score boosting #39

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
12 commits
Select commit Hold shift + click to select a range
94e1e31
rust
coszio Apr 16, 2025
169f0d9
Sync OpenAPI
coszio Apr 16, 2025
740e0f8
python
coszio Apr 16, 2025
5a6d9e8
curl
coszio Apr 16, 2025
2b2de7c
Sync OpenAPI
coszio Apr 16, 2025
94c8f8f
go
coszio Apr 17, 2025
6147f14
csharp
coszio Apr 17, 2025
657b97b
java
coszio Apr 17, 2025
7b38843
typescript
coszio Apr 22, 2025
7a335d1
sync openapi
coszio Apr 22, 2025
f93cb6f
Sync OpenAPI
coszio Apr 22, 2025
ebbc5ea
revert v1.13
coszio Apr 22, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 7 additions & 7 deletions fern/apis/master/openapi-overrides.yml
View file
Open in desktop

Large diffs are not rendered by default.

249 changes: 218 additions & 31 deletions fern/apis/v1.14.x/openapi-overrides.yml
View file
Open in desktop

Large diffs are not rendered by default.

63 changes: 63 additions & 0 deletions snippets/csharp/query_points.cs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -61,3 +61,66 @@ await client.QueryAsync(
collectionName: "{collection_name}",
query: Sample.Random
);

// Score boost depending on payload conditions (as of 1.14.0)
await client.QueryAsync(
collectionName: "{collection_name}",
prefetch:
[
new PrefetchQuery { Query = new float[] { 0.01f, 0.45f, 0.67f }, Limit = 100 },
],
query: new Formula
{
Expression = new SumExpression
{
Sum =
{
"$score",
new MultExpression
{
Mult = { 0.5f, Match("tag", ["h1", "h2", "h3", "h4"]) },
},
new MultExpression { Mult = { 0.25f, Match("tag", ["p", "li"]) } },
},
},
},
limit: 10
);

// Score boost geographically closer points (as of 1.14.0)
await client.QueryAsync(
collectionName: "{collection_name}",
prefetch:
[
new PrefetchQuery { Query = new float[] { 0.01f, 0.45f, 0.67f }, Limit = 100 },
],
query: new Formula
{
Expression = new SumExpression
{
Sum =
{
"$score",
WithExpDecay(
new()
{
X = new GeoDistance
{
Origin = new GeoPoint { Lat = 52.504043, Lon = 13.393236 },
To = "geo.location",
},
Scale = 5000,
}
),
},
},
Defaults =
{
["geo.location"] = new Dictionary<string, Value>
{
["lat"] = 48.137154,
["lon"] = 11.576124,
},
},
}
);
59 changes: 54 additions & 5 deletions snippets/curl/query_points.sh
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
# Query nearest by ID
curl -X POST \
curl -X POST \
'http://localhost:6333/collections/collection_name/points/query' \
--header 'api-key: <api-key-value>' \
--header 'Content-Type: application/json' \
Expand All @@ -8,7 +8,7 @@ curl -X POST \
}'

# Recommend on the average of these vectors
curl -X POST \
curl -X POST \
'http://localhost:6333/collections/collection_name/points/query' \
--header 'api-key: <api-key-value>' \
--header 'Content-Type: application/json' \
Expand All @@ -35,7 +35,7 @@ curl -X POST \
}'

# Fusion query
curl -X POST \
curl -X POST \
'http://localhost:6333/collections/collection_name/points/query' \
--header 'api-key: <api-key-value>' \
--header 'Content-Type: application/json' \
Expand Down Expand Up @@ -71,7 +71,7 @@ curl -X POST \
}'

# 2-stage query
curl -X POST \
curl -X POST \
'http://localhost:6333/collections/collection_name/points/query' \
--header 'api-key: <api-key-value>' \
--header 'Content-Type: application/json' \
Expand Down Expand Up @@ -107,7 +107,7 @@ curl -X POST \
}'

# Random sampling (as of 1.11.0)
curl -X POST \
curl -X POST \
'http://localhost:6333/collections/collection_name/points/query' \
--header 'api-key: <api-key-value>' \
--header 'Content-Type: application/json' \
Expand All @@ -116,3 +116,52 @@ curl -X POST \
"sample": "random"
}
}'

# Score boost depending on payload conditions (as of 1.14.0)
curl -X POST \
'http://localhost:6333/collections/collection_name/points/query' \
--header 'api-key: <api-key-value>' \
--header 'Content-Type: application/json' \
--data-raw '{
"prefetch": {
"query": [0.2, 0.8, ...], // <-- dense vector
"limit": 50
}
"query": {
"formula": {
"sum": [
"$score,
{ "mult": [ 0.5, { "key": "tag", "match": { "any": ["h1", "h2", "h3", "h4"] } } ] },
{ "mult": [ 0.25, { "key": "tag", "match": { "any": ["p", "li"] } } ] }
]
}
}
}'

# Score boost geographically closer points (as of 1.14.0)
curl -X POST \
'http://localhost:6333/collections/collection_name/points/query' \
--header 'api-key: <api-key-value>' \
--header 'Content-Type: application/json' \
--data-raw '{
"prefetch": { "query": [0.2, 0.8, ...], "limit": 50 },
"query": {
"formula": {
"sum": [
"$score",
{
"gauss_decay": {
"x": {
"geo_distance": {
"origin": { "lat": 52.504043, "lon": 13.393236 } // Berlin
"to": "geo.location"
}
},
"scale": 5000 // 5km
}
}
]
},
"defaults": { "geo.location": {"lat": 48.137154, "lon": 11.576124} } // Munich
}
}'
61 changes: 61 additions & 0 deletions snippets/go/query_points.go
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -93,4 +93,65 @@ func query() {
panic(err)
}
fmt.Println("Query results: ", points)

// Score boost depending on payload conditions (as of 1.14.0)
points, err = client.Query(context.Background(), &qdrant.QueryPoints{
CollectionName: "{collection_name}",
Prefetch: []*qdrant.PrefetchQuery{
{
Query: qdrant.NewQuery(0.01, 0.45, 0.67),
},
},
Query: qdrant.NewQueryFormula(&qdrant.Formula{
Expression: qdrant.NewExpressionSum(&qdrant.SumExpression{
Sum: []*qdrant.Expression{
qdrant.NewExpressionVariable("$score"),
qdrant.NewExpressionMult(&qdrant.MultExpression{
Mult: []*qdrant.Expression{
qdrant.NewExpressionConstant(0.5),
qdrant.NewExpressionCondition(qdrant.NewMatchKeywords("tag", "h1", "h2", "h3", "h4")),
},
}),
qdrant.NewExpressionMult(&qdrant.MultExpression{
Mult: []*qdrant.Expression{
qdrant.NewExpressionConstant(0.25),
qdrant.NewExpressionCondition(qdrant.NewMatchKeywords("tag", "p", "li")),
},
}),
},
}),
}),
})

// Score boost geographically closer points (as of 1.14.0)
client.Query(context.Background(), &qdrant.QueryPoints{
CollectionName: "{collection_name}",
Prefetch: []*qdrant.PrefetchQuery{
{
Query: qdrant.NewQuery(0.2, 0.8),
},
},
Query: qdrant.NewQueryFormula(&qdrant.Formula{
Expression: qdrant.NewExpressionSum(&qdrant.SumExpression{
Sum: []*qdrant.Expression{
qdrant.NewExpressionVariable("$score"),
qdrant.NewExpressionExpDecay(&qdrant.DecayParamsExpression{
X: qdrant.NewExpressionGeoDistance(&qdrant.GeoDistance{
Origin: &qdrant.GeoPoint{
Lat: 52.504043,
Lon: 13.393236,
},
To: "geo.location",
}),
}),
},
}),
Defaults: qdrant.NewValueMap(map[string]any{
"geo.location": map[string]any{
"lat": 48.137154,
"lon": 11.576124,
},
}),
}),
})
}
83 changes: 83 additions & 0 deletions snippets/java/query_points.java
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -90,3 +90,86 @@
.setQuery(sample(Sample.Random))
.build())
.get();

// Score boost depending on payload conditions (as of 1.14.0)
client
.queryAsync(
QueryPoints.newBuilder()
.setCollectionName("{collection_name}")
.addPrefetch(
PrefetchQuery.newBuilder()
.setQuery(nearest(0.01f, 0.45f, 0.67f))
.setLimit(100)
.build())
.setQuery(
formula(
Formula.newBuilder()
.setExpression(
sum(
SumExpression.newBuilder()
.addSum(variable("$score"))
.addSum(
mult(
MultExpression.newBuilder()
.addMult(constant(0.5f))
.addMult(
condition(
matchKeywords(
"tag",
List.of("h1", "h2", "h3", "h4"))))
.build()))
.addSum(mult(MultExpression.newBuilder()
.addMult(constant(0.25f))
.addMult(
condition(
matchKeywords(
"tag",
List.of("p", "li"))))
.build()))
.build()))
.build()))
.build())
.get();

// Score boost geographically closer points (as of 1.14.0)
client
.queryAsync(
QueryPoints.newBuilder()
.setCollectionName("{collection_name}")
.addPrefetch(
PrefetchQuery.newBuilder()
.setQuery(nearest(0.01f, 0.45f, 0.67f))
.setLimit(100)
.build())
.setQuery(
formula(
Formula.newBuilder()
.setExpression(
sum(
SumExpression.newBuilder()
.addSum(variable("$score"))
.addSum(
expDecay(
DecayParamsExpression.newBuilder()
.setX(
geoDistance(
GeoDistance.newBuilder()
.setOrigin(
GeoPoint.newBuilder()
.setLat(52.504043)
.setLon(13.393236)
.build())
.setTo("geo.location")
.build()))
.setScale(5000)
.build()))
.build()))
.putDefaults(
"geo.location",
value(
Map.of(
"lat", value(48.137154),
"lon", value(11.576124))))
.build()))
.build())
.get();
47 changes: 46 additions & 1 deletion snippets/python/query_points.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -54,5 +54,50 @@
# Random sampling (as of 1.11.0)
sampled = client.query_points(
collection_name="{collection_name}",
query=models.SampleQuery(sample=models.Sample.Random)
query=models.SampleQuery(sample=models.Sample.RANDOM)
)

# Score boost depending on payload conditions (as of 1.14.0)
tag_boosted = client.query_points(
collection_name="{collection_name}",
prefetch=models.Prefetch(
query=[0.2, 0.8, ...], # <-- dense vector
limit=50
),
query=models.FormulaQuery(
formula=models.SumExpression(sum=[
"$score",
models.MultExpression(mult=[0.5, models.FieldCondition(key="tag", match=models.MatchAny(any=["h1", "h2", "h3", "h4"]))]),
models.MultExpression(mult=[0.25, models.FieldCondition(key="tag", match=models.MatchAny(any=["p", "li"]))])
]
))
)

# Score boost geographically closer points (as of 1.14.0)
geo_boosted = client.query_points(
collection_name="{collection_name}",
prefetch=models.Prefetch(
query=[0.2, 0.8, ...], # <-- dense vector
limit=50
),
query=models.FormulaQuery(
formula=models.SumExpression(sum=[
"$score",
models.GaussDecayExpression(
gauss_decay=models.DecayParamsExpression(
x=models.GeoDistance(
geo_distance=models.GeoDistanceParams(
origin=models.GeoPoint(
lat=52.504043,
lon=13.393236
), # Berlin
to="geo.location"
)
),
scale=5000 # 5km
)
)
]),
defaults={"geo.location": models.GeoPoint(lat=48.137154, lon=11.576124)} # Munich
)
)
Loading